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On this page

  • Overview
    • 1. Overview
    • 2. Key Features
    • 3. Technical Implementation
    • 4. Project Structure
    • 5. Data Sources
    • 6. Project Links
    • 7. Session Info
    • 8. GitHub Repository
    • 9. References
    • 10. Citation

RWFD Supply Chain Analytics Dashboard

Interactive visualization of manufacturing logistics metrics, focusing on cost analysis and warehouse utilization

R Programming
Shiny
Supply Chain
2025
An interactive R Shiny dashboard that transforms complex supply chain data into actionable insights. Features real-time KPIs, cost analysis, and warehouse performance metrics with dynamic filtering and visualizations.
Author

Steven Ponce

Published

February 16, 2025

Figure 1: RWFD Supply Chain Dashboard: An interactive Shiny application featuring logistics KPIs, cost analysis, and warehouse performance metrics. The dashboard provides insights into shipping costs, warehouse utilization, and service level performance.

Overview

1. Overview

The RWFD Supply Chain Dashboard is an interactive R Shiny application designed to analyze and visualize manufacturing logistics data. The dashboard focuses on two main areas:

  1. Overview Dashboard

    • Real-time tracking of total shipping costs
    • Average cost per KG analysis
    • Warehouse utilization monitoring
    • On-time delivery performance metrics
  2. Cost Analysis Dashboard

    • Detailed cost breakdown by location
    • Unit cost analysis with efficiency quadrants
    • Performance matrix for warehouse comparison

2. Key Features

  1. Interactive Elements

    • Dynamic filtering by warehouse location
    • Carrier-specific analysis
    • Service level breakdowns
    • Real-time metric updates
  2. Visualizations

    • Interactive route cost analysis
    • Storage cost comparisons
    • Transport mode breakdowns
    • Service level distribution
    • Efficiency matrix heatmap
  3. Data Downloads

    • CSV exports for all visualizations
    • Customizable data filtering
    • Comprehensive metrics export

3. Technical Implementation

The dashboard is built using:

  • R Shiny: Core web framework
  • bslib: Modern Bootstrap 5 styling
  • tidyverse: Data processing
  • ggiraph: Interactive visualizations
  • DT: Data tables
  • Additional packages: scales, glue, janitor

4. Project Structure

├── app.R              # Main application
├── global.R           # Global settings
├── modules/
│   ├── overview/      # Overview dashboard
│   └── cost_analysis/ # Cost analysis
└── R/
    └── utils/         # Helper functions

5. Data Sources

The application processes four key datasets:

  1. Order List: Transaction data

    • Shipping details
    • Order metrics
    • Service levels
  2. Freight Rates: Pricing data

    • Carrier rates
    • Route costs
    • Service options
  3. Warehouse Data: Facility metrics

    • Storage costs
    • Utilization rates
    • Capacity limits
  4. Warehouse Capacities: Infrastructure data

    • Daily capacity limits
    • Regional information
    • Facility type and status

6. Project Links

  • Live Dashboard: RWFD Supply Chain Dashboard

  • Source Code: GitHub Repository

7. Session Info

Expand for Session Info
R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22631)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

loaded via a namespace (and not attached):
 [1] htmlwidgets_1.6.4 compiler_4.4.0    fastmap_1.2.0     cli_3.6.3        
 [5] htmltools_0.5.8.1 tools_4.4.0       rstudioapi_0.17.1 yaml_2.3.10      
 [9] rmarkdown_2.29    knitr_1.49        jsonlite_1.8.9    xfun_0.49        
[13] digest_0.6.37     rlang_1.1.4       renv_1.0.3        evaluate_1.0.1   

8. GitHub Repository

Expand for GitHub Repo

Access the GitHub repository here

9. References

Expand for References
  1. Data originally from:
    • Kalganova, Tatiana; Dzalbs, Ivars (2019). Supply Chain Logistics Problem Dataset. Brunel University London. Dataset

    • Accessed via: RWFD Real World Fake Data

10. Citation

Expand for References

To cite this dashboard: - Ponce, S. (2024). RWFD Supply Chain Dashboard Shiny Application

Back to top
Source Code
---
title: "RWFD Supply Chain Analytics Dashboard"
subtitle: "Interactive visualization of manufacturing logistics metrics, focusing on cost analysis and warehouse utilization"
description: "An interactive R Shiny dashboard that transforms complex supply chain data into actionable insights. Features real-time KPIs, cost analysis, and warehouse performance metrics with dynamic filtering and visualizations."  
author: "Steven Ponce"
date: "2025-02-16"
categories: ["R Programming", "Shiny", "Supply Chain", "2025"]
tags: [
  "r-shiny",
  "supply-chain-analytics",
  "dashboard",
  "data-visualization",
  "logistics",
  "interactive-dashboard",
  "warehouse-analytics",
  "cost-analysis",
  "business-intelligence",
  "bslib",
  "tidyverse",
  "ggiraph",
  "performance-metrics",
  "kpi-monitoring"
]
image: "thumbnails/sa_2025-02-16.png"
format:
  html:
    toc: true
    toc-depth: 5
    code-link: true
    code-fold: true
    code-tools: true
    code-summary: "Show code"
    self-contained: true
    theme: 
      light: [flatly, assets/styling/custom_styles.scss]
      dark: [darkly, assets/styling/custom_styles_dark.scss]
editor_options:  
  chunk_output_type: inline
execute: 
  freeze: true                                                  
  cache: true                                                   
  error: false
  message: false
  warning: false
  eval: true
# filters:
#   - social-share
# share:
#   
#   permalink: "https://stevenponce.netlify.app/projects/standalone_visualizations/sa_2025-02-16.html"
#   description: "Explore an interactive R Shiny dashboard for supply chain analytics, featuring real-time KPIs, cost analysis, and warehouse performance visualization. Built with #rstats #shiny #dataviz"
#   twitter: true
#   linkedin: true
#   email: true
#   facebook: false
#   reddit: false
#   stumble: false
#   tumblr: false
#   mastodon: true
#   bsky: true
---

```{r setup}
#| label: setup
#| include: false

knitr::opts_chunk$set(
  dev = "png",
  fig.width = 9,
  fig.height = 10,
  dpi = 320
)
```

![RWFD Supply Chain Dashboard: An interactive Shiny application featuring logistics KPIs, cost analysis, and warehouse performance metrics. The dashboard provides insights into shipping costs, warehouse utilization, and service level performance.](sa_2025-02-16.png){#fig-1}

### <mark> __Overview__ </mark>  

#### 1. Overview

The RWFD Supply Chain Dashboard is an interactive R Shiny application designed to analyze and visualize manufacturing logistics data. The dashboard focuses on two main areas:

a. **Overview Dashboard**

   - Real-time tracking of total shipping costs
   - Average cost per KG analysis
   - Warehouse utilization monitoring
   - On-time delivery performance metrics

b. **Cost Analysis Dashboard**

   - Detailed cost breakdown by location
   - Unit cost analysis with efficiency quadrants
   - Performance matrix for warehouse comparison

#### 2. Key Features 

a. **Interactive Elements**

   - Dynamic filtering by warehouse location
   - Carrier-specific analysis
   - Service level breakdowns
   - Real-time metric updates

b. **Visualizations**

   - Interactive route cost analysis
   - Storage cost comparisons
   - Transport mode breakdowns
   - Service level distribution
   - Efficiency matrix heatmap

c. **Data Downloads**

   - CSV exports for all visualizations
   - Customizable data filtering
   - Comprehensive metrics export

#### 3. Technical Implementation

The dashboard is built using:

- **R Shiny**: Core web framework
- **bslib**: Modern Bootstrap 5 styling
- **tidyverse**: Data processing
- **ggiraph**: Interactive visualizations
- **DT**: Data tables
- Additional packages: scales, glue, janitor

#### 4. Project Structure

```
├── app.R              # Main application
├── global.R           # Global settings
├── modules/
│   ├── overview/      # Overview dashboard
│   └── cost_analysis/ # Cost analysis
└── R/
    └── utils/         # Helper functions
```

#### 5. Data Sources

The application processes four key datasets:

a. **Order List**: Transaction data

   - Shipping details
   - Order metrics
   - Service levels

b. **Freight Rates**: Pricing data

   - Carrier rates
   - Route costs
   - Service options

c. **Warehouse Data**: Facility metrics

   - Storage costs
   - Utilization rates
   - Capacity limits

c. **Warehouse Capacities**: Infrastructure data

   - Daily capacity limits
   - Regional information
   - Facility type and status

#### 6. Project Links

- **Live Dashboard**: [RWFD Supply Chain Dashboard](https://0l6jpd-steven-ponce.shinyapps.io/RWFD_supply_chain/)

- **Source Code**: [GitHub Repository](https://github.com/poncest/RWFD_supply_chain)


#### 7. Session Info

::: {.callout-tip collapse="true"}
##### Expand for Session Info

```{r, echo = FALSE}
#| eval: true
#| warning: false

sessionInfo()
```
:::

#### 8. GitHub Repository

::: {.callout-tip collapse="true"}
##### Expand for GitHub Repo
 
[Access the GitHub repository here](https://github.com/poncest/RWFD_supply_chain)
:::


#### 9. References

::: {.callout-tip collapse="true"}
##### Expand for References

1. Data originally from:
   - Kalganova, Tatiana; Dzalbs, Ivars (2019). Supply Chain Logistics Problem Dataset. Brunel University London. [Dataset](https://doi.org/10.17633/rd.brunel.7558679.v2)
   
   - Accessed via: [RWFD Real World Fake Data](https://sonsofhierarchies.com/real-world-fake-data/)

:::


#### 10. Citation

::: {.callout-tip collapse="true"}
##### Expand for References

To cite this dashboard:
   - Ponce, S. (2024). RWFD Supply Chain Dashboard [Shiny Application](https://github.com/poncest/RWFD_supply_chain)

:::

© 2024 Steven Ponce

Source Issues